精准科学地评价中国城市受新冠疫情的短期影响及恢复情况并揭示其时空变化特征，可为“常态化”疫情防控阶段城市经济形势研判和城市恢复提供有力支撑。利用夜间灯光数据（NTL）、PMI人口迁徙数据、空气污染等多源数据构建疫情影响和恢复指标，以城市爆发疫情为基准，使用地理统计和同心环分析，对在不同时空尺度下对城市经济的异质性影响进行实证分析。结果表明，使用多源数据整合指标可以有效地反映疫情对城市造成的影响及城市恢复趋势；在空间分布上，住宅区及郊外受影响较小，中心商业区及工业区受影响较大。

Accurate and scientific evaluation of the short-term impact and recovery of Chinese cities from COVID-19 and revealing its spatio-temporal change characteristics can provide strong support for the study and assessment of urban economic situation and urban recovery in the “normal” epidemic prevention and control stage. We used the multi-source data, such as VIIRS nighttime light, PMI population migration data and air pollution, to construct epidemic impact and recovery indicators. Based on the outbreak in cities, we used geographical statistics and concentric-ring analysis to conduct empirical analysis on the urban economy heterogeneity at different spatio-temporal scales. The results show that the multi-source data integration index can effectively reflect the impact of epidemic on the city and the trend of urban recovery. In terms of spatial distribution, residential areas and suburbs are less affected, while central business and industrial areas are more affected.